Optimization of Cutting Parameters Based on Pareto Genetic Algorithm
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    Abstract:

    Based on the Pareto genetic algorithm, an algorithm was proposed for the cutting parameters selection and optimization to solve the decisionmaking problems of the cutting parameters in a computer aided process planning (CAPP) system. First, a multi-objective model was built by analysis of restraint with cutting speed and feed as optimization variables and cutting efficiency and the tool life as optimization objectives. Second, the selection operator was improved. In order to ensure the search direction, a non-inferior set was set up to save Pareto optimal solutions which were generated by competition during evolutionary processes. The crowing mechanism based on niche technology was established to keep population diversity. And then, genes were recombined by means of mixed crossover operator and step-size mutation operator and an optimal set which distributed uniformly along the Pareto front was obtained after a few times iteration. Experiments results showed that this algorithm was feasible and effective.

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